Interference management and network performance optimization in small cells

ABSTRACT

A method of configuring small cell base stations in a cellular network is disclosed. A constraint on a performance-related metric associated with at least a portion of the cellular network is received. In some embodiments, the constraint on the performance-related metric comprises a constraint on a performance-related metric associated with one or more macrocells. Measurement data from one or more small cell base stations is received via a control interface. One or more optimized values of one or more parameters associated with one or more small cell base stations are searched. The searching is based at least in part on the received measurement data and subject to the constraint on the performance-related metric associated with the at least a portion of the cellular network. The one or more optimized values of the one or more parameters to the associated small cell base stations are transmitted.

CROSS REFERENCE TO OTHER APPLICATIONS

This application is a continuation of co-pending U.S. patent applicationSer. No. 13/867,993 entitled INTERFERENCE MANAGEMENT AND NETWORKPERFORMANCE OPTIMIZATION IN SMALL CELLS filed Apr. 22, 2013, whichclaims priority to U.S. Provisional Patent Application No. 61/637,174entitled INTERFERENCE MANAGEMENT IN LTE HETNETS VIA SON-ENABLED SMALLCELLS filed Apr. 23, 2012 both of which are incorporated herein byreference for all purposes.

BACKGROUND OF THE INVENTION

Internet Protocol based cellular networks are increasingly migratingfrom flat to hierarchical architectures in order to address capacity andcoverage issues. A hierarchical cellular network includes macrocells andsmall cells. However, the deployment challenges of small cells haveprecluded their widespread adoption to date.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments of the invention are disclosed in the followingdetailed description and the accompanying drawings.

FIG. 1 illustrates an embodiment of a hierarchical cellular networkarchitecture 100.

FIG. 2 illustrates an embodiment of a cellular network manager 202 forautomatically and dynamically configuring and updating parameters of thesmall cell base stations 204 in a cellular network to optimize theoverall network performance of the cellular network.

FIG. 3 illustrates an embodiment of a cellular network manager 202 forautomatically and dynamically configuring and updating parameters of thesmall cell base stations 204 in a cellular network to optimize theoverall network performance of the cellular network.

FIG. 4 is a flow chart illustrating an embodiment of a process 400 forautomatically and dynamically configuring and updating parameters of thesmall cell base stations 204 in a cellular network to optimize theoverall network performance of the cellular network.

FIG. 5 a illustrates that without cell range extension, a small cellbase station serves few users, while the macrocell is overloaded.

FIG. 5 b illustrates that cell range extension techniques may be used tooffload traffic from a macrocell to a small cell, thereby allowing moreefficient spatial reuse of the cellular spectrum.

DETAILED DESCRIPTION

The invention can be implemented in numerous ways, including as aprocess; an apparatus; a system; a composition of matter; a computerprogram product embodied on a computer readable storage medium; and/or aprocessor, such as a processor configured to execute instructions storedon and/or provided by a memory coupled to the processor. In thisspecification, these implementations, or any other form that theinvention may take, may be referred to as techniques. In general, theorder of the steps of disclosed processes may be altered within thescope of the invention. Unless stated otherwise, a component such as aprocessor or a memory described as being configured to perform a taskmay be implemented as a general component that is temporarily configuredto perform the task at a given time or a specific component that ismanufactured to perform the task. As used herein, the term ‘processor’refers to one or more devices, circuits, and/or processing coresconfigured to process data, such as computer program instructions.

A detailed description of one or more embodiments of the invention isprovided below along with accompanying figures that illustrate theprinciples of the invention. The invention is described in connectionwith such embodiments, but the invention is not limited to anyembodiment. The scope of the invention is limited only by the claims andthe invention encompasses numerous alternatives, modifications andequivalents. Numerous specific details are set forth in the followingdescription in order to provide a thorough understanding of theinvention. These details are provided for the purpose of example and theinvention may be practiced according to the claims without some or allof these specific details. For the purpose of clarity, technicalmaterial that is known in the technical fields related to the inventionhas not been described in detail so that the invention is notunnecessarily obscured.

Internet Protocol based (IP-based) cellular networks, including cellularnetworks based on the fourth-generation (4G) Long Term Evolution (LTE)standard, face significant capacity and coverage challenges due to therapidly growing demand for mobile broadband and the limited spectrumavailable to support such a demand. IP-based cellular networks areincreasingly migrating from flat to hierarchical architectures in orderto address capacity and coverage issues.

Most second-generation (2G) and third-generation (3G) cellular networkshave relatively flat architectures, including mostly macrocells withhigher power (e.g., 10 to 40 Watts of transmit power) cellular basestations. While such large cells offer the benefits of fast deploymentand wide area coverage, they do not provide high capacity due to theirnon-aggressive frequency reuse.

FIG. 1 illustrates an embodiment of a hierarchical cellular networkarchitecture 100. In contrast to a flat cellular network, a hierarchicalcellular network includes macrocell(s) 102 and various levels of smallcells 104 (e.g., femtocells, picocells, and microcells) with lower powercellular base stations. Small cell base stations transmit at much lowerpowers and hence have smaller coverage areas. This enables moreefficient spatial reuse of spectrum, leading to higher aggregatethroughput than in macrocell-only networks. Small cells 104 also bringtheir base stations closer to the mobile user equipment (UE) 106,resulting in better coverage and less power consumption at both the basestations and the devices. In addition, small cells 104 do not causesignificant interference to macrocell users for a number of reasons. AUE 106 associates with a macrocell base station only if the receivedsignal strength from the macrocell base station on the downlink is atleast as high as the received signal strength from a small cell basestation. On the uplink, the channel gain from a UE 106 to a small cell104 is typically large. Hence, the UEs 106 can achieve their desiredperformance with a lower transmit power to the small cell base station,resulting in minimal interference to macrocell 102. Moreover, offloadingusers to small cells 104 leads to higher throughput for all users,including those associated with macrocell 102, since more resources aremade available at macrocell 102 and the resources may be used moreefficiently. These small cell benefits coupled with low cost havebrought about a paradigm shift in 4G cellular architectures from flat tohierarchical, with macrocells deployed for coverage and small cellsdeployed for capacity, coverage, and power efficiency.

At the same time, the deployment challenges of small cells haveprecluded their widespread adoption to date. Typically, the deploymentof macrocells in the field is both time-consuming and costly. Forexample, the network operator or service provider typically deploys amacrocell by sending a team of engineers to the field to configure, makemeasurements, debug, and fine-tune the configuration parameters of thebase stations and the associated networks. Since the number of smallcells that are needed to be deployed in a given area is much larger thanthe number of macrocells in the area, deploying the small cells bysending a team of engineers in the field to configure and fine-tune theparameters of the base stations would be both time and cost-prohibitive.In addition, femtocell base stations are often placed in arbitrarylocations by the end-users, rendering the manual configuration byengineers impractical. Moreover, configuring the small cells in such amanner is likely non-optimal, in part because the configuration isdetermined by trial and error and based on limited information. Thealternative—deploying the small cells using pre-configuredparameters—also has a number of drawbacks: for example, the interferencecaused by the small cells to the macrocells may be so high in somesituations that it severely impacts the overall performance and serviceof the entire cellular network; resources that are used by themacrocells and the small cells may not be shared optimally andefficiently; additionally, handovers between the macrocells and thesmall cells may not be performed reliably.

FIG. 2 illustrates an embodiment of a cellular network manager 202 forautomatically and dynamically configuring and updating parameters of thesmall cell base stations 204 in a cellular network to optimize theoverall network performance of the cellular network. As will bedescribed in greater detail below, cellular network manager 202 may beused for intelligent and dynamic self-configuration, self-optimization,and self-healing of the small cells in order to optimize the overallnetwork performance of the cellular network.

As shown in FIG. 2, the cellular network is a heterogeneous network(HetNet) including macrocell base stations 206 and various levels ofsmall cell base stations 204 (e.g., femtocell, picocell, and microcellbase stations) with various levels of transmit power. The cellularnetwork may be any IP-based cellular networks, including cellularnetworks based on the 4G LTE standard and cellular networks based on anyfuture-generation cellular standards. The cellular network provideswireless service to a plurality of UEs 210. UEs 210 may be cellularphones, laptop computers equipped with mobile broadband adapters,tablets, and the like.

In some embodiments, cellular network manager 202 connects to small cellbase stations 204 via an IP network 208 and provides service to smallcell base stations 204 as a network server. In some embodiments, asoftware agent is installed on each small cell base station 204, and thesoftware agent is used to communicate with and obtain services fromcellular network manager 202.

Cellular network manager 202 allows network operators to optimize thetradeoff between the performance benefits of the small cells versustheir impact on the macrocells (e.g., the amount of interference causedby the small cells on the macrocells). In some embodiments, cellularnetwork manager 202 automatically and dynamically configures theparameters of small cell base stations 204 to optimize the HetNet'soverall network performance, subject to any predefined constraintsdictated by the network operators.

The predefined constraints may include any constraints onperformance-related metrics, including but not limited to constraints oninterference caused to the macrocells by the small cells, throughput,delay, number of dropped calls, coverage, the ability to offload trafficto Wi-Fi networks, and the like. For example, the network operator ofthe cellular network may specify a maximum threshold (e.g., 6 dBm) forthe amount of interference that the small cells may cause to themacrocells. In one example, the network operator may specify a minimumaggregate throughput or a maximum percentage drop in throughput in aparticular macrocell. In another example, the network operator of thecellular network may specify a minimum percentage of end-users having aminimum threshold of data throughput. In another example, the networkoperator of the cellular network may specify a maximum number orpercentage of dropped calls within a predefined period of time. In yetanother example, the network operator may specify a minimum percentageof end-users having coverage. Note that the above examples are providedfor illustrative purposes only. Therefore, the present application isnot limited to these specific examples only.

With continued reference to FIG. 2, measurements are periodicallycollected by small cell base stations 204 from different UEs 210 and/orfrom other base stations (e.g., macrocell base stations), and thesemeasurements are then sent by small cell base stations 204 to cellularnetwork manager 202. Measurements may include, but are not limited to,signal strength, interference indicators, channel quality, throughput,packet error rate, and load information. Cellular network manager 202then computes the configuration parameters for at least some of thesmall cell base stations 204 that optimize network performancetradeoffs, such as minimum interference, maximum throughput, and maximumcoverage, based on the measurement data and the predefined constraintsspecified by the network operator. For example, the configurationparameters may be determined using different searching or optimizationtechniques. Configuration parameters for small cell base stations 204include frequency parameters, channel allocation parameters, fractionalfrequency reuse parameters, power parameters, interference coordinationparameters, antenna parameters, time-division parameters, cell rangeextension (CRE) parameters, and the like. The computed configurationparameters for small cell base stations 204 are then transmitted fromcellular network manager 202 to small cell base stations 204 forself-configuration, self-optimization, or self-healing of the smallcells.

In some embodiments, the measurements and the interfaces for connectingthe base stations to cellular network manager 202 are standards-basedmeasurements and interfaces. For example, small cell base stations 204may be connected to cellular network manager 202 via 3^(rd) GenerationPartnership Project (3GPP) compliant interfaces. The 3GPP standardspecifies a set of measurements that are periodically collected by thebase stations from the UEs and other base stations via the standardizedX2 interfaces. The X2 interfaces connect neighboring base stations in apeer-to-peer fashion to assist handover and provide a means for rapidcoordination of radio resources. In some other embodiments, themeasurements or the interfaces for connecting the base stations tocellular network manager 202 are non-standards based measurements andinterfaces.

As described above, measurements are periodically collected by smallcell base stations 204 from different UEs 210 and/or from other basestations (e.g., macrocell base stations). For example, a small cell basestation 204 may receive measurement data from a UE 210 that is connectedto the small cell base station 204, and the measurement or performancedata is information corresponding to the UE 210 itself or informationcorresponding to any neighboring base stations that the UE 210 can hearfrom. A small cell base station 204 may also receive measurements orperformance information directly (e.g., via X2 interfaces) from itsneighboring base stations, including its neighboring small cell basestations 204 and neighboring macrocell base stations 206. Oneillustrative example of measurement data that can be collected directlyby a small cell base station 204 from a neighboring base station is theUplink Interference Overload Indication (OI) message exchanged over theX2 interface. Via an OI message, a neighboring base station may inform asmall cell base station 204 of the average uplink interference plusnoise that the neighboring base station experiences in individualphysical resource blocks (PRBs). The average uplink interference plusnoise is indicated as one of three levels—low, medium, or high levels ofinterference plus noise. A small cell base station 204 may also obtainmeasurements or performance information from neighboring base stationsby periodically entering a network listen/monitor mode. In the networklisten mode, the small cell base station may decode broadcastinformation from neighboring base stations to determine properties oftransmissions in its RF vicinity. The set of broadcast messages that thesmall cell base station can decode depends on how much of the UEfunctionality is implemented at the small cell base station. In someembodiments, the amount of measurement data that are collected by smallcell base stations 204 may vary depending on the level of cooperationbetween small cell base stations 204 and their neighboring basestations. For example, if a particular macrocell base station 206 iscooperative with a particular small cell base station 204, thenadditional or non-standards based measurements may be sent by themacrocell base station 206 to the small cell base station 204. In somecases, these additional measurement data may be used by the optimizationtechniques performed by cellular network manager 202 to further optimizethe overall network performance.

FIG. 3 illustrates an embodiment of a cellular network manager 202 forautomatically and dynamically configuring and updating parameters of thesmall cell base stations 204 in a cellular network to optimize theoverall network performance of the cellular network. In this embodiment,cellular network manager 202 manages and dynamically configures aplurality of small cell base stations 204 using the various techniquesdiscussed above. In addition, a second cellular network manger 302manages and dynamically configures a plurality of macrocell basestations 206. Cellular network manager 202 and cellular network manager302 may exchange information or measurement data. For example, cellularnetwork manager 302 may transmit the interference information of amacrocell base station 206 to cellular network manager 202. In someembodiments, cellular network manager 202 and cellular network manager302 are integrated into a single module for automatically anddynamically configuring and updating parameters of both small cell basestations 204 as well as macrocell base stations 206, thereby optimizingthe network performance associated with both the small cells and themacrocells.

As described above, different optimization techniques may be used forsearching the configuration parameters for small cell base stations 204.A plurality of configuration parameters may be optimized at the sametime. In addition, any combination of configuration parameters may beoptimized at the same time. For example, power parameters, fractionalfrequency reuse parameters, cell range extension parameters of one ormore small cell base stations 204 may be optimized at the same time. Insome cases, an optimal solution set subject to a specific set ofpredefined constraints may not be achievable, and relaxation techniquesmay be applied. In some embodiments, in addition to a predefinedconstraint (e.g., maximum permissible interference) for theoptimization, statistics associated with the predefined constraint maybe provided by the network operator. For example, the network operatormay specify that the probability of interference exceeding thepredefined constraint be less than 1%, thus allowing the optimizationtechniques to compute a solution set while meeting the predefinedconstraint as close as possible.

Cellular network manager 202 allows the network operator to deploy smallcells while keeping their impact to the macrocells to levels acceptableto the operator. Limits of degradation in the macrocells may bespecified, and then small cell base stations 204 may be deployed to meetthose limits. Small cell base stations 204 may be deployed in multiplestages. For example, after a small cell base station 204 is deployed,the network operator may relax the predefined constraints (e.g.,increase the interference constraint experienced by a macrocell) in aniterative approach to achieve increasingly higher aggregate networkperformance.

FIG. 4 is a flow chart illustrating an embodiment of a process 400 forautomatically and dynamically configuring and updating parameters of thesmall cell base stations 204 in a cellular network to optimize theoverall network performance of the cellular network. In someembodiments, process 400 is a process that runs on cellular networkmanager 202.

At 402, a constraint on a performance-related metric associated with oneor more macrocells is received. Performance-related metrics includeinterference in the macrocells attributed to the small cells,throughput, delay, volume or probability of dropped calls, coverage, andthe like. In some embodiments, the constraint is configurable by thenetwork operator via a graphical user interface (GUI) or byconfiguration files. For example, the network operator may configure amaximum threshold for the amount of interference that the small cellsmay cause to the macrocells for interference management.

At 404, measurement data is received from one or more small cell basestations. In some embodiments, the measurement data may be collected bya small cell base station from the UEs connected to the small cell basestation, and the measurement data may include information regarding aparticular UE or regarding neighboring cells/base stations that the UEcan detect on the cellular network. In some embodiments, the measurementdata may be collected by a small cell base station from otherneighboring base stations, including neighboring small cell basestations or neighboring macrocell base stations. For example, thesemeasurement data may be sent from a neighboring base station to thesmall cell base station via standard-based interfaces, such as the X2interfaces. The measurement data may include signal strength,interference indicators, channel quality, throughput, packet error rate,load information, and the like. The measurement data may bestandards-based measurements or non-standards based measurements.

At 406, the optimized values of parameters associated with one or moresmall cell base stations that optimize the cellular network performanceare searched. As the cellular network manager receives measurement dataabout different portions of the entire cellular network, the measurementdata may be used by the cellular network manager to compute theparameters of the small cell base stations that can optimize networkperformance in a global sense, thereby achieving superior networkperformance. The search is based on the measurement data received fromthe small cell base stations and subject to the received constraint(s)on the performance-related metric.

The cellular network performance may be defined by different metrics. Insome embodiments, the metrics may be a set of network performanceoptimization goals defined by a network operator. The goals may includeincreasing the average network throughput, increasing the geometric meanthroughput, reducing interference, reducing outage probability,increasing coverage, improving fairness, supporting specificquality-of-service metrics for high-priority traffic, and the like. Thenetwork performance optimization goals may be performance goalscorresponding to the small cell networks only, the macrocell networksonly, or both the small cell networks and the macrocell networks. Insome emdodiments, the network operator may weigh the network performanceoptimization goals of different portions of the entire cellular network(i.e., the cellular network including both small cells and marcocells)differently. For example, the network operator may optimize a weightedcombination of the small cell network performance optimization goals andthe macrocell network performance optimization goals

Different parameters may be dynamically adjusted to optimize the overallcellular network performance. The parameters may include frequencychannel parameters, fractional frequency reuse parameters, transmitpower parameters, interference coordination parameters, antennaparameters, time-division parameters, cell range extension parameters,handoff information, and the like. The frequency parameters may beoptimized such that different bands of frequency (as opposed to only thehigher frequency bands) may be allocated to a small cell base station.For example, instead of allocating high frequency bands to small cellsand low frequency bands to macrocells, cellular network manager 202 maydivide the spectrum into finer granularity, and allocate the frequencychannels to the small cell base stations and the macrocell base stationsfor optimized performance.

In some embodiments, the parameters that may be dynamically optimizedinclude parameters corresponding to an orthogonal frequency divisionmultiplexing (OFDM) based system (e.g., an LTE system). As will bedescribed in greater detail below, different resources may be allocatedfor different physical channels (data or control channels) for uplinkand downlink. The transmission powers on the different channels in timeand frequency may be dynamically optimized. Furthermore, the physicalcell ID of a cell may be dynamically optimized.

The basic unit of resource in an OFDM system is a subcarrier in thefrequency domain and a symbol in the time domain.

The physical channels for Downlink (DL) include:

-   -   a. Physical Broadcast Channel (PBCH)    -   b. Physical Control Format Indicator Channel (PCFICH)    -   c. Physical Downlink Control Channel (PDCCH)    -   d. Physical Downlink Shared Channel (PDSCH)    -   e. Physical Hybrid ARQ Indicator Channel (PHICH)

The control channels (PDCCH, PHICH, PCFICH) are time multiplexed withPDSCH. On the DL, the resource allocation includes determining thefollowing:

-   -   (i) What fraction of symbols are allocated for PDCCH    -   (ii) the transmission power used for PDCCH    -   (iii) the transmission power profile across frequency for PDSCH    -   (iv) the scheduling of almost blank subframes when only a small        number of reference signals are transmitted on the data        resources to mitigate interference at neighboring cells

The physical channels for the uplink include:

-   -   a. Physical Uplink Control Channel (PUCCH)    -   b. Physical Uplink Shared Channel (PUSCH)    -   c. Physical Random Access Channel (PRACH)    -   d. Sounding Reference Signal (SRS).

PUCCH and PUSCH are multiplexed in the frequency domain, whereas PUSCHand SRS are multiplexed in the time domain. Resource allocation includesdetermining the following:

-   -   (i) What fraction of bandwidth is allocated to PUCCH    -   (ii) PUCCH transmission power control parameters for UEs    -   (iii) How often SRS is transmitted and over how many RBs.    -   (iv) PUCCH transmission power control parameters for UEs: this        can be a periodic function of time    -   (v) PUSCH high and low interference subcarriers in frequency

In some embodiments, the parameters that may be dynamically optimizedinclude physical cell IDs. A physical cell ID ranges from 0 to 503 anddetermines the scrambling for primary and secondary synchronizationsignals, as well as the transmission characteristics of the cellreference signal (CRS). Hence, if a base-station knows the physical cellid of neighboring cells, it can make an optimized choice of its own cellid.

Different optimization techniques may be employed by a cellular networkmanager for searching the optimized parameters. In some embodiments, thenetwork performance optimization goals are evaluated based at least inpart on the measurement data received from the small cell base stations.The set of network performance optimization goals may be represented byan objective function or a cost function in an optimization problem. Anoptimized parameter resulting from the search is a feasible solution oroptimal solution that minimizes (or maximizes) the objective functionsubject to different constraints. Since multiple types of parameters maybe adjusted simultaneously during a search, different techniques tocombat interference, increase throughput, or maximize coverage may beleveraged at the same time. For example, instead of determining transmitpower and frequency reuse individually or locally, they can be optimizedsimultaneously in a global sense.

With continued reference to FIG. 4, at 408, the optimized values of theparameters associated with the small cell base stations are transmittedto the small cell base stations. The parameters may be used by the smallcell base stations for self-configuration, self-optimization, andself-healing, such that the base stations can collectively form aself-organizing network.

The parameters may be used to initialize a small cell base station thathas been recently installed. For example, after a small cell basestation is first installed, the small cell base station collects initialmeasurement data and sends the data to the cellular network manager. Thecellular network manager then computes the parameters for a small cellbase station and sends them to the small cell base station forself-configuration.

The parameters may be used to re-configure an existing small cell basestation. When the existing small cell base station connects to thecellular network manager for the first time, the existing small cellbase station is treated as a new installation for the purpose of networkoptimization. The cellular network manager computes new parameters forthe existing small cell base station based on the received measurementdata from the existing small cell base station and other base stations,and it sends the new parameters to the existing small cell base stationfor reconfiguration.

The parameters may be used to periodically update the parameters of anexisting small cell base station. The parameters are computed based ondynamic, real-time measurements made or collected periodically by thesmall cell base station.

The parameters may also be used by the small cell base stations forself-healing any network topology changes. For example, a networktopology change may be caused by the failure of a base station. Thecellular network manager detects the failure, and the parameters of thesurrounding small cell base stations are automatically adjusted to fillin the resulting coverage hole. In another example, a network topologychange may be caused by new base stations being installed on thecellular network. The network topology change may be detected by thecellular network manager, which is triggered by the detection toinitiate a new search.

As described above, standard-based measurement data may be collecteddirectly by a small cell base station 204 from a neighboring basestation via standards-based interfaces. One illustrative example is theinter-cell interference coordination (ICIC) mechanisms that have beenincorporated into the 3GPP LTE standard for managing interference andoptimizing offloading of data traffic to small cells. Messages areexchanged between base stations over the X2 interface; these messagesinclude, but are not limited to, the Relative Narrowband Transmit Power(RNTP) messages, the Uplink Interference Overload Indication (OI), andthe Uplink High Interference Indication (HII).

In one illustrative example, cellular network manager 202 minimizes asmall cell's downlink and uplink interferences to a macrocell asfollows:

-   -   After receiving an RNTP message from a macrocell, a small cell        base station may reduce its downlink interference to the        macrocell's UEs by either not using or lowering its downlink        transmit power in the PRBs in which the macrocell base station        uses high transmit power. This increases the signal to        interference plus noise ratio (SINR) of the cell-edge users of        the macrocell when their traffic is scheduled on these PRBs. For        the macrocell users that are not on the cell edge, the small        cell causes lower interference on all PRBs since the small        cell's transmit power is much lower (by approximately 16 dB)        than that of the macrocell.    -   On the uplink, if the small cell receives an HII message or an        OI message, the small cell base station may limit the        interference it causes to the macrocells by lowering the        transmit power of its UEs on any PRB for which either the HII or        the OI message from the macrocell has a high value. The transmit        power can be chosen based on measurement reports obtained from        the UE (which can be used to estimate path loss to the        macrocell) and the power control mechanism.

In another illustrative example, cellular network manager 202 optimizesthe network performance as follows:

-   -   When a small cell base station receives measurement reports from        a UE that is associated with the small cell base station and is        lying on the cell edge of a macrocell, the measurement reports        give an estimate of the macrocell received power on the cell        edge. The RNTP message allows the small cell base station to        estimate a lower bound on the transmit power of the macrocell        for cell edge users. The small cell base station may lower its        power in PRBs in which the macrocell has a higher RNTP, thereby        providing a means for cell edge users to achieve a certain        minimum SINR.    -   The small cell base station can enable better load balancing by        suggesting cell range extension (CRE) bias values to the        macrocell based on messages received by it from the macrocell.

As described above, cell range extension parameters are examples ofconfigurable parameters that can be optimized by cellular networkmanager 202.

FIG. 5 a illustrates that without cell range extension, a small cellbase station serves few users, while the macrocell is overloaded. Asshown in FIG. 5 a, the number of UEs 512 connected to a small cell basestation 508 is typically much smaller than the number of UEs 506connected to a macrocell base station 502, because the transmit power ofmacrocell base station 502 is much larger than that of the small cellbase station 508.

FIG. 5 b illustrates that cell range extension techniques may be used tooffload traffic from a macrocell to a small cell, thereby allowing moreefficient spatial reuse of the cellular spectrum. Cell range extensionis implemented by configuring a UE to trigger measurement reportingwhenever its measured signal quality from a neighboring cell basestation (typically a small cell base station) is within a CRE biasthreshold with respect to the serving cell base station's referencesignal received power (RSRP). For example, the bias threshold may be setto a few dBm below the RSRP of the serving cell base station, so as tobias the UE to be handed off to the neighboring small cell. If the biasthreshold is set to zero, then there is no preferential offloading ofUEs from the macrocell to the small cell. Higher bias threshold valuesresult in more offloading to small cells. Cellular network manager 202may optimize the overall network performance by dynamically andautomatically adjusting the CRE parameters (together with otherparameters) to balance the load of different portions of the cellularnetwork.

In some embodiments, a Wi-Fi access point (AP) is integrated orco-located with a small cell base station. Offloading data from thecellular network to Wi-Fi networks is an attractive mechanism tomitigate the spectrum scarcity faced by cellular networks for a numberof reasons. For example, the spectrum allocated for Wi-Fi networks issignificantly greater than that allocated for cellular networks.Moreover, the spectrum allocated to Wi-Fi networks is unlicensed, thusincurring no additional spectrum licensing costs to the Wi-Fi providers.Cellular network manager 202 may further optimize the overall networkperformance by dynamically and automatically adjusting the CREparameters within the cellular network, such that the UEs are biased tobe preferentially handed off to a neighboring small cell base stationintegrated with a Wi-Fi AP than to a neighboring small cell base stationthat is not integrated or co-located with a Wi-Fi AP.

Although the foregoing embodiments have been described in some detailfor purposes of clarity of understanding, the invention is not limitedto the details provided. There are many alternative ways of implementingthe invention. The disclosed embodiments are illustrative and notrestrictive.

What is claimed is:
 1. (canceled)
 2. A method of configuring small cellbase stations in a cellular network, comprising: receiving a constrainton a performance-related metric associated with at least a portion ofthe cellular network; receiving measurement data from one or more smallcell base stations via a control interface; searching, using aprocessor, for one or more optimized values of one or more parametersassociated with one or more small cell base stations, wherein thesearching is based at least in part on the received measurement data andsubject to the constraint on the performance-related metric associatedwith the at least a portion of the cellular network, wherein the one ormore parameters comprise a parameter corresponding to a cell rangeextension bias towards a small cell base station, and wherein thesearching optimizes the parameter corresponding to the cell rangeextension bias based on whether the small cell base station can offloaddata traffic to a Wi-Fi network; and transmitting the one or moreoptimized values of the one or more parameters to the associated smallcell base stations.
 3. The method of claim 2, where the constraint onthe performance-related metric comprises a constraint on aperformance-related metric associated with one or more macrocells. 4.The method of claim 2, wherein the searching is based on a set ofnetwork performance optimization goals.
 5. The method of claim 4,wherein the network optimization goal comprises one of the following:increasing the average network throughput, increasing the geometric meanthroughput, reducing interference, reducing outage probability,increasing coverage, improving fairness, and supporting specificquality-of-service metrics for high-priority traffic.
 6. The method ofclaim 4, wherein the set of network performance optimization goalscomprises one of the following: network performance optimization goalscorresponding to small cells, network performance optimization goalscorresponding to macrocells, and a weighted combination of networkperformance optimization goals corresponding to small cells andmacrocells.
 7. The method of claim 2, wherein the performance-relatedmetric comprises one of the following: interference, throughput, delay,number of dropped calls, and coverage.
 8. The method of claim 2, whereinthe measurement data comprises measurement data collected by a smallcell base station from a user equipment (UE) connected to the small cellbase station.
 9. The method of claim 8, wherein the measurement datacollected by the small cell base station comprises informationcorresponding to the UE.
 10. The method of claim 8, wherein themeasurement data collected by the small cell base station comprisesinformation corresponding to a neighboring base station that the UE canhear from.
 11. The method of claim 2, wherein the measurement datacomprises measurement data collected by a small cell base station from aneighboring base station.
 12. The method of claim 2, wherein themeasurement data comprises one of the following: signal strength,interference, channel quality, throughput, packet error rate, and loadinformation.
 13. The method of claim 2, wherein the one or moreparameters comprise a parameter corresponding to one of the following:frequency channel, fractional frequency reuse, power, interferencecoordination, antenna, time-division, cell range extension, and handoff.14. The method of claim 2, wherein two or more parameters are jointlyoptimized.
 15. The method of claim 2, further comprising: detectingwhether a base station has failed or whether a new base station has beeninstalled; and initiating the search in response to the detection. 16.The method of claim 2, wherein the searching is performed periodicallyand wherein the measurement data is received periodically.
 17. Themethod of claim 2, further comprising: receiving additional measurementdata from another manager managing a macrocell base station; and whereinthe searching of the one or more optimized values of the one or moreparameters is further based on the additional measurement data.
 18. Acellular network manager for configuring small cell base stations in acellular network, comprising: a control interface in communication witha plurality of small cell base stations; a processor; and a memorystoring a set of network performance optimization goals, wherein thememory is coupled with the processor, and wherein the memory isconfigured to provide the processor with instructions which whenexecuted cause the processor to: receive a constraint on aperformance-related metric associated with at least a portion of thecellular network; receive measurement data from one or more small cellbase stations; search for one or more optimized values of one or moreparameters associated with one or more small cell base stations, whereinthe searching is based at least in part on the received measurement dataand subject to the constraint on the performance-related metricassociated with the at least a portion of the cellular network, whereinthe one or more parameters comprise a parameter corresponding to a cellrange extension bias towards a small cell base station, and wherein thesearching optimizes the parameter corresponding to the cell rangeextension bias based on whether the small cell base station can offloaddata traffic to a Wi-Fi network; and transmit the one or more optimizedvalues of the one or more parameters to the associated small cell basestations.
 19. The system of claim 18, where the constraint on theperformance-related metric comprises a constraint on aperformance-related metric associated with one or more macrocells. 20.The system of claim 18, wherein the searching is based on a set ofnetwork performance optimization goals.
 21. The system of claim 20,wherein the network optimization goal comprises one of the following:increasing the average network throughput, increasing the geometric meanthroughput, reducing interference, reducing outage probability,increasing coverage, improving fairness, and supporting specificquality-of-service metrics for high-priority traffic.
 22. The system ofclaim 20, wherein the set of network performance optimization goalscomprises one of the following: network performance optimization goalscorresponding to small cells, network performance optimization goalscorresponding to macrocells, and a weighted combination of networkperformance optimization goals corresponding to small cells andmacrocells.
 23. The system of claim 18, wherein the performance-relatedmetric comprises one of the following: interference, throughput, delay,number of dropped calls, and coverage.
 24. The system of claim 18,wherein the measurement data comprises measurement data collected by asmall cell base station from a user equipment (UE) connected to thesmall cell base station.
 25. The system of claim 24, wherein themeasurement data collected by the small cell base station comprisesinformation corresponding to the UE.
 26. The system of claim 24, whereinthe measurement data collected by the small cell base station comprisesinformation corresponding to a neighboring base station that the UE canhear from.
 27. The system of claim 18, wherein the measurement datacomprises measurement data collected by a small cell base station from aneighboring base station.
 28. The system of claim 18, wherein themeasurement data comprises one of the following: signal strength,interference, channel quality, throughput, packet error rate, and loadinformation.
 29. The system of claim 18, wherein the one or moreparameters comprise a parameter corresponding to one of the following:frequency channel, fractional frequency reuse, power, interferencecoordination, antenna, time-division, cell range extension, and handoff.30. The system of claim 18, wherein two or more parameters are jointlyoptimized.
 31. The system of claim 18, wherein the memory is furtherconfigured to provide the processor with instructions which whenexecuted cause the processor to: detect whether a base station hasfailed or whether a new base station has been installed; and initiatethe search in response to the detection.
 32. The system of claim 18,wherein the searching is performed periodically and wherein themeasurement data is received periodically.
 33. The system of claim 18,wherein the memory is further configured to provide the processor withinstructions which when executed cause the processor to: receiveadditional measurement data from another manager managing a macrocellbase station; and wherein the searching of the one or more optimizedvalues of the one or more parameters is further based on the additionalmeasurement data.
 34. A computer program product for configuring smallcell base stations in a cellular network, the computer program productbeing embodied in a non-transitory computer readable storage medium andcomprising computer instructions for: receiving a constraint on aperformance-related metric associated with at least a portion of thecellular network; receiving measurement data from one or more small cellbase stations via a control interface; searching, using a processor, forone or more optimized values of one or more parameters associated withone or more small cell base stations, wherein the searching is based atleast in part on the received measurement data and subject to theconstraint on the performance-related metric associated with the atleast a portion of the cellular network, wherein the one or moreparameters comprise a parameter corresponding to a cell range extensionbias towards a small cell base station, and wherein the searchingoptimizes the parameter corresponding to the cell range extension biasbased on whether the small cell base station can offload data traffic toa Wi-Fi network; and transmitting the one or more optimized values ofthe one or more parameters to the associated small cell base stations.35. The computer program product of claim 34, where the constraint onthe performance-related metric comprises a constraint on aperformance-related metric associated with one or more macrocells.